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http://dspace.cityu.edu.hk/handle/2031/7433
Title: | Look over here: attention-directing composition of manga elements |
Authors: | Cao, Ying (曹迎) Lau, Rynson, W. H. Chan, Antoni B. |
Department: | Department of Computer Science |
Issue Date: | Aug-2014 |
Award: | Cao Ying won the First Runner-up in the Graduate Student Research Paper Competition 2013-2014 organized by the IEEE (HK) Computational Intelligence Chapter. |
Supervisor: | Dr. Lau, Rynson, W. H. and Dr. Chan, Antoni B. |
Description: | The award winning work was published (ACM Reference Format): Cao, Y., Lau, R., Chan, A. 2014. Look Over Here: Attention-Directing Composition of Manga Elements. ACM Trans. Graph. 33, 4, Article 94 (July 2014), 11 pages. DOI = 10.1145/2601097.2601183 http://doi.acm.org/10.1145/2601097.2601183. |
Type: | Research paper |
Abstract: | Picture subjects and text balloons are basic elements in comics, working together to propel the story forward. Japanese comics artists often leverage a carefully designed composition of subjects and balloons (generally referred to as panel elements) to provide a continuous and fluid reading experience. However, such a composition is hard to produce for people without the required experience and knowledge. In this paper, we propose an approach for novices to synthesize a composition of panel elements that can effectively guide the reader’s attention to convey the story. Our primary contribution is a probabilistic graphical model that describes the relationships among the artist’s guiding path, the panel elements, and the viewer attention, which can be effectively learned from a small set of existing manga pages. We show that the proposed approach can measurably improve the readability, visual appeal, and communication of the story of the resulting pages, as compared to an existing method. We also demonstrate that the proposed approach enables novice users to create higher-quality compositions with less time, compared with commercially available programs. |
Appears in Collections: | Student Works With External Awards |
Files in This Item:
File | Size | Format | |
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award_winning_work.html | 161 B | HTML | View/Open |
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